Artificial Intelligence Chip Reshaping Every Industry Worldwide

Artificial intelligence is becoming a massive trend across the world due to the availability and generation of enormous digital content on a daily basis. The proliferation of smart mobile devices, easy availability of internet, and the Internet of Things (IoT) are some of the major factors responsible for this data explosion across industry and consumer segments.

The advent of smart homes, smart workplaces, and smart cities concepts are further complementing the skyrocketing growth of artificial intelligence technology. In today’s digital world, information is the key for modern day companies to be successful and to achieve sustainable growth in the fierce competitive scenario across industries.

The paradigm shift towards digitization is allowing companies to reap great benefits and resulting in more revenue generation opportunities. Most industries, especially in the service sector rely deeply on data analytics to gain useful business and consumer insights. These insights help companies to reduce costs and improve operational efficiencies and thus enable them to remain competitive in the market.

Companies all around the world have been continuously automating their business processes in order to keep pace with the fast-changing digital world.

With advancements in artificial intelligence (AI) technology and the introduction of application-specific custom AI chips, businesses now have the capability to collect real-time data about their business processes and their customers. Artificial intelligence and data analytics allows businesses to transform this data into actionable insights.

There are numerous use-cases of AI technology available in the market today and they are increasing at a fast pace across various industry verticals. The major applications of artificial intelligence in diverse industry verticals include machine learning (ML), natural language processing (NLP), expert systems, automated speech recognition, AI planning, and computer vision.

All the major industry verticals across are globe including BFSI, retail, IT, telecom, automotive, healthcare, media & entertainment, manufacturing, government, and energy are embracing and investing aggressively in disruptive technologies such as artificial intelligence, IoT, big data, and predictive analytics. This interest from various industries is mainly driven by the successful uses cases of AI in the banking, financial services, and insurance sector.

With the ever-increasing applications of artificial intelligence, the concerns regarding data privacy and data security are also rising majorly due to lack of sufficient data protection laws in most countries.

The proper functioning and future growth of artificial intelligence are heavily dependent on the data collected from various sources. For this, businesses and customers have to allow access to their personal and confidential information to AI systems and devices.

Increasing usage of digital services and data storage on the cloud has further raised data security and privacy concerns among consumers and businesses. To address these concerns, AI technology and solutions providers are developing systems/chips with inbuilt security features to boost customers’ confidence.

One of the major future trend evolving in the artificial intelligence chip marketplace is the application of AI chips in edge devices such as smartphones, drones, and self-driving cars.

AI accelerators are evolving at an unprecedented rate and new hardware platforms are also being optimized to facilitate greater autonomy to edge devices.

The proliferation of smartphone-embedded AI processors by tech giants such as Apple, Samsung, and Google is gaining traction and driving the adoption of AI chips in edge devices.

AI robotics is another noteworthy application of artificial intelligence which will drive the penetration of AI chips in future applications such as self-driving cars, drones, smart appliances, and industrial IoT.

Tech giants such as NVIDIA, Apple, Google, Huawei, and Intel are showing huge interest and investing heavily in edge inferencing applications of artificial intelligence chips. With these developments, it is expected that edge applications are going to be the future of artificial intelligence in the coming years.

Another fast evolving trend in the Artificial Intelligence Chip industry is the development of Application-specific integrated circuits (ASICs) for specific industry applications. ASICs are task specific and less flexible, but they have superior performance in comparison to other available AI chips.

In terms of efficiency also, ASICs are more efficient in performance/dollar and performance/watt terms. There are multiple companies including Microsoft, Google, Amazon, Apple, and Tesla that are working on the development of some type of ASIC chips for artificial intelligence applications.

The future of AI chips lies in these custom and application-specific ASICs. These custom AI chipset architectures offer a diverse range of AI applications including machine learning, deep learning, and natural language processing among others for both training and inference applications.

These tech-savvy, robust and ‘think-big’ startups are making the AI market more competitive which is leading to more innovations and technology improvements. With all the technological advancements happening in the field of artificial intelligence and investments made by big tech companies, artificial intelligence technology holds a promising future in the coming years.

Ankita is currently working as Team Lead in Electronics and Semiconductor domain
of The Insight Partners, a premier market research and consulting firm. She is an
Electronics Engineer with 4+ years of experience in multiple segment including
Business Research and Consulting, Report Writing, Data Mining, Go-to-Market
Strategy, and Business Research & Forecast.
Prior to the current company she was employed with MarketsandMarkets,
manufacturing and construction Consulting team, and was responsible for executing consulting as well
as syndicate projects, and preparing proposals.
She is an Electronics and Communication engineering graduate from Rajiv Gandhi Technical University
and have two years of past experience in manufacturing division.

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